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clustering variables [35-36]. Researchers would then be able to determine if consumers'
preferences for production systems varied by age, education or employment status. The
Kolmogorov-Smirnov test was used to check whether the clustering variables were normally
distributed and the Kruskal Wallis test was used to compare clusters.
Further analysis employing multidimensional scaling (MDS) was used to obtain “perceptual
mapping of consumers' preferences for production systems. By transforming consumer
judgments of overall preferences into distance represented in multidimensional space, MDS
plots the three production systems and five criteria on a map such that those systems and
criteria that are perceived to be very similar to each other are placed near each other on the
map, and those systems and criteria that are perceived to be very different from each other are
placed far away from each other on the map. In this way MDS provides a visual representation
of the pattern of proximities (i.e., similarities) among the set of production system and the set
of criteria employed in their assessment [36].
6.2. Results and discussion
Consumers were grouped into three clusters. The mean of the variables used in the analysis
is presented by the clusters in Table 1. There were statistically significant differences among
clusters on the variables age, education and employment. The mean age (40.85) is the lowest
in Cluster 1 and the highest (80.35) in Cluster 3. Education level is the highest (4.94) in Cluster
1 and lowest in cluster 3 (2.41). Employment status changes from employed in Cluster 1 (2.13)
to unemployed in Cluster 3 (2.97). Cluster 1 is labeled “Young professional”, while the cluster
2 and cluster 3 are labeled “Older-technician” and “Oldest-unemployed” respectively.
Clusters
Kruskal Wallis Test
Variables
1
2
3
Chi-Square
Asymp. Sig
Age
40.85
63.48
80.35
191.962
0.000
Education
*
4.94
4.32
2.41
29.596
0.000
Employment
**
2.13
2.52
2.97
69.077
0.000
*
1: Less than high school, 11: Professional/doctorate degree;
**
1: Part time, 2: Full time, 3: Unemployed
Table 1.
Cluster analysis by age, education and employment
Table 2 displays the number of consumers by the clusters. The data show that 52.1 percent of
consumers are “young professional”, 33.5 percent are “older-technician”, while the “oldest-
unemployed” accounts for 14.4 percent.
In the AHP Model, consumers were asked to assess conventional, sustainable and organic
production systems, taking into account the ability of each to generate benefits related to
environmental conservation, food safety, food quality, wellness and community economic
development. The AHP model for assessing preferences for production systems in terms of
